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Authors: Susana M. Vieira 1 ; Alexandra Moutinho 1 ; Margarida Solas 1 ; José F. Loureiro 1 ; Maria B. Silva 1 ; Sara Zorro 2 ; Luís Patrão 3 ; Joaquim Gabriel 4 and Jorge Silva 2

Affiliations: 1 Universidade de Lisboa, Portugal ; 2 Universidade de Lisboa and Universidade da Beira Interior, Portugal ; 3 Universidade da Beira Interior, Portugal ; 4 Universidade do Porto, Portugal

ISBN: 978-989-758-263-9

Keyword(s): Light-sport Aviation, Classification, Prediction, Neural Networks Model, Decision Support System.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Business Analytics ; Cardiovascular Technologies ; Computational Intelligence ; Computing and Telecommunications in Cardiology ; Data Engineering ; Decision Support Systems ; Decision Support Systems, Remote Data Analysis ; Engineering Applications ; Enterprise Information Systems ; Health Engineering and Technology Applications ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Knowledge-Based Systems ; Robotics and Automation ; Signal Processing, Sensors, Systems Modeling and Control ; Soft Computing ; Symbolic Systems

Abstract: Several applications require humans to be in high-altitude environments, whether for recreational purposes, like mountaineering or light sport aviation, or for labour, as miners. Although in these conditions the monitoring of physiological variables is, per se, of interest, the direct correlation of these variables with altitude itself is not usually explored towards the development of decision-support systems and/or critical event alarms. This paper proposes two neural networks approaches to assess and explore this correlation. One, based on dynamic SISO models, estimates physiological variables using the aircraft pressure altitude as input. A second approach uses static MISO networks to classify the flight stage (and therefore the altitude variation) from physiological variables. Both models were developed and validated using real data acquired in hypobaric chamber tests simulating a real flight. The good results obtained indicate the viability of the approach.

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Paper citation in several formats:
M. Vieira, S.; Moutinho, A.; Solas, M.; Loureiro, J.; B. Silva, M.; Zorro, S.; Patrão, L.; Gabriel, J. and Silva, J. (2017). Relating Aircraft Altitude with Pilot’s Physiological Variables: Towards Increasing Safety in Light-sport Aviation.In Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-263-9, pages 359-364. DOI: 10.5220/0006476903590364

@conference{icinco17,
author={Susana M. Vieira. and Alexandra Moutinho. and Margarida Solas. and José F. Loureiro. and Maria B. Silva. and Sara Zorro. and Luís Patrão. and Joaquim Gabriel. and Jorge Silva.},
title={Relating Aircraft Altitude with Pilot’s Physiological Variables: Towards Increasing Safety in Light-sport Aviation},
booktitle={Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2017},
pages={359-364},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006476903590364},
isbn={978-989-758-263-9},
}

TY - CONF

JO - Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Relating Aircraft Altitude with Pilot’s Physiological Variables: Towards Increasing Safety in Light-sport Aviation
SN - 978-989-758-263-9
AU - M. Vieira, S.
AU - Moutinho, A.
AU - Solas, M.
AU - Loureiro, J.
AU - B. Silva, M.
AU - Zorro, S.
AU - Patrão, L.
AU - Gabriel, J.
AU - Silva, J.
PY - 2017
SP - 359
EP - 364
DO - 10.5220/0006476903590364

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